Title : 
Interactive Genetic Algorithms with Grey Modeling for Individuals Fitness
         
        
            Author : 
Guo Guang-song ; Chen Liang-ji
         
        
            Author_Institution : 
Sch. of Mechatron. Eng., Zheng Zhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
         
        
        
        
        
        
        
            Abstract : 
In order to apply the interactive Genetic Algorithms (GA) into complicated optimization problem, an interactive Genetic Algorithms with grey prediction for fitness of evolutionary individuals is proposed, in which the uncertainty of evolutionary individuals is measured by gery modeling. By predicting the grey modeling, the reliableness which reflecting the measurement is abstracted. On this basis, the formulation of fitness adjustment is proposed. The algorithm is applied to a fashion evolutionary design system, test results show that it can find more satisfactory solutions per generation.
         
        
            Keywords : 
genetic algorithms; grey systems; complicated optimization problem; evolutionary individuals fitness; evolutionary individuals uncertainty; fashion evolutionary design system; fitness adjustment formulation; grey modeling; grey prediction; interactive genetic algorithms; Algorithm design and analysis; Convergence; Forecasting; Genetic algorithms; Humans; Predictive models; Uncertainty; fitness; genetic algorithm; grey modeling; interaction;
         
        
        
        
            Conference_Titel : 
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
         
        
            Conference_Location : 
Hangzhou
         
        
            Print_ISBN : 
978-1-4673-0689-8
         
        
        
            DOI : 
10.1109/ICCSEE.2012.43